Objective

A vision-based human kinematic modeling system is built using the Temporal
Shape-From-Silhouettes Algorithms (details can be found
here ). The acquired kinematic model is then used to
perform non-invasive motion capture of motions from video sequences using an idea
similar to that used in our Temporal SFS Algorithms.
Technical details of this project can be found in the documents listed below:

Human Kinematic Modeling System

There are three tasks to the human kinematic modeling system. The first task recovers all the joint locations
of the body. The second task acquires precise shape information. The final task merges the joint and shape
together to form a articulated model of the person.

Algorithms

Results

Human Markerless Motion Capture

The kinematic model acquired above is used to track new motions of the person
by an Image-based Articulated Object Tracking Algorithm. Eight cameras are used in each sequence.
Mpeg videos showing tracking results of two synthetic data
sets (KICK and PUNCH sequences) and five real data sets of simple motions (STILLMARCH and AEROBICS sequences)
and complex ones (KUNGFU, THROW, SLOWDANCE and STEP-FLEX sequences) are included below.